Human bone marrow hematopoietic stem cells are
increased in frequency and myeloid-biased with age
Wendy W. Panga,1, Elizabeth A. Priceb, Debashis Sahooa, Isabel Beermanc, William J. Maloneyd, Derrick J. Rossic,
Stanley L. Schrierb, and Irving L. Weissmana,1
aInstitute for Stem Cell Biology and Regenerative Medicine, Ludwig Center for Stem Cell Research, and Department of Pathology,bDepartment of
Internal Medicine, Division of Hematology, anddDepartment of Orthopaedic Surgery, Stanford University, Stanford, CA 94305; andcImmune Disease
Institute, Harvard Medical School, Boston, MA 02115
Contributed by Irving L. Weissman, October 20, 2011 (sent for review June 14, 2011)
In the human hematopoietic system, aging is associated with de-
creased bone marrow cellularity, decreased adaptive immune sys-
tem function, and increased incidence of anemia and other
hematological disorders and malignancies. Recent studies in mice
suggest that changes within the hematopoietic stem cell (HSC)
population during aging contribute significantly to the manifes-
tation of these age-associated hematopoietic pathologies. Though
the mouse HSC population has been shown to change both
quantitatively and functionally with age, changes in the human
HSC and progenitor cell populations during aging have been
incompletely characterized. To elucidate the properties of an aged
human hematopoietic system that may predispose to age-associ-
ated hematopoietic dysfunction, we evaluated immunopheno-
typic HSC and other hematopoietic progenitor populations from
healthy, hematologically normal young and elderly human bone
marrow samples. We found that aged immunophenotypic human
HSC increase in frequency, are less quiescent, and exhibit myeloid-
biased differentiation potential compared with young HSC. Gene
expression profiling revealed that aged immunophenotypic hu-
man HSC transcriptionally up-regulate genes associated with cell
cycle, myeloid lineage specification, and myeloid malignancies.
These age-associated alterations in the frequency, developmental
potential, and gene expression profile of human HSC are similar to
those changes observed in mouse HSC, suggesting that hemato-
poietic aging is an evolutionarily conserved process.
erarchy of committed progenitors that ultimately give rise to
mature blood cells (1). Though the mechanisms of aging in the
hematopoietic system are comprised of a combination of cell-in-
trinsic and -extrinsic causes that ultimately alter the generation
and function of mature blood lineages, there is increasing evi-
dence that implicates alterations within the HSC population as
one of the mechanisms behind hematopoietic aging. We and
others have found that as mice age, their HSC numbers increase,
but competitive repopulation ability is reduced, suggesting a de-
crease in mouse HSC function with age (2–7). Additionally, el-
derly mouse HSC exhibit a marked decrease in lymphopoiesis and
increase in myelopoiesis (2, 6). In the mouse, we and others have
identified distinct clonal subtypes of HSC that differentially re-
spond to external cytokine stimuli and exhibit lineage bias upon
transfer to irradiated hosts (8–13). The majority of HSC from
elderly mice are myeloid biased, whereas most HSC from young
mice are balanced in lymphopoiesis and myelopoiesis (8–13).
In humans, age-associated hematopoietic changes include de-
the incidence of myelodysplastic syndromes, myeloproliferative
disorders,and myeloid malignancies (18).In humanbone marrow,
the HSC population is highly enriched within the Lin−CD34+
CD38−CD90+CD45RA−population (19–24). Previous studies
addressing the age-associated changes in human HSC have relied
on indirect evaluations of stem and progenitor populations and
ematopoiesis is initiated by hematopoietic stem cells (HSC)
that can self-renew and progressively differentiate into a hi-
have therefore been less quantitative than studies of mouse HSC
from fetal liver, to cord blood, to adult bone marrow (25), and
some indirect evidence suggests reductions in stem cell reserves
with age (26, 27), particularly in the context of anemia (28).
Clinically, in the setting of bone marrow transplantation, in-
creasing donor age correlates with increasing transplant-related
mortality (29). Few studies have evaluated the frequency of bone
marrow progenitor populations directly: one study found that the
number of CD34+bone marrow cells decreases with age (30),
whereas another study found that the frequency of CD34+CD38−
bone marrow cells increases with age (31). However, CD34+and
CD34+CD38−bone marrow populations are both heterogeneous,
only a small fraction of which are HSC.
Therefore, to more precisely identify changes within the stem
cell compartments that contribute to human hematopoietic aging,
we evaluated the putative human HSC compartment (immuno-
phenotypically defined as Lin−CD34+CD38−CD90+CD45RA−)
from healthy, young (20–35 y of age) human bone marrow sam-
ples (hereafter referred to as young HSC) and healthy elderly
(65+ y of age) human bone marrow samples (hereafter referred
to as elderly HSC). We characterized, by flow cytometry, the
frequency, distribution, and cell-cycle profile of immunopheno-
typic HSC and other hematopoietic progenitor populations, and
we found that aged immunophenotypic human HSC are in-
creased in frequency and are less quiescent than young HSC. We
sorted immunophenotypic human HSC from young and elderly
bone marrow samples and tested their ability to proliferate and
differentiate in vitro and in vivo. Both young and elderly
immunophenotypic human HSC were able to generate lymphoid
and myeloid progeny in culture, but elderly HSC exhibited sig-
nificantly myeloid-biased differentiation potential compared with
young HSC under equal conditions. Elderly immunophenotypic
human HSC xenotransplanted into immunodeficient mice did
not engraft or generate lymphoid progeny as efficiently as young
human HSC. We also performed gene expression profiling of
sorted young and elderly immunophenotypic human HSC. Our
results suggest that a number of mechanisms behind the phenotype
of hematopoietic aging are transcriptionally regulated at the level
of diverse subsets of HSC.
Author contributions: W.W.P., E.A.P., D.J.R., S.L.S., and I.L.W. designed research; W.W.P.,
I.B., and D.J.R. performed research; W.J.M. contributed new reagents/analytic tools;
W.W.P., E.A.P., D.S., S.L.S., and I.L.W. analyzed data; and W.W.P., S.L.S., and I.L.W.
wrote the paper.
Conflict of interest statement: W.J.M. is on the board of and owns stock and options in
Stemedica Cell Technologies, Inc. I.L.W. is on the board of StemCells, Inc., and owns stock
in Amgen, Inc.
Freely available online through the PNAS open access option.
Data deposition: The data reported in this paper have been deposited in the Gene Ex-
pression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE32719).
1To whom correspondence may be addressed. E-mail: email@example.com or irv@
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| December 13, 2011
| vol. 108
| no. 50www.pnas.org/cgi/doi/10.1073/pnas.1116110108
To directly characterize human HSC during aging, we first
quantified by flow cytometry the frequency of immunophenotypic
human HSC (Lin−CD34+CD38−CD90+CD45RA−) in hemato-
logically normal young and elderly bone marrow samples (Fig.
1A). We found that elderly bone marrow contain increased fre-
quency of HSC within the CD34+population (Fig. 1B) as well as
within the bone marrow mononuclear fraction (SI Appendix, Fig.
S1), consistent with a recent finding in a small number of samples
showing an age-associated increase in frequency of HSC (32).
Quantification of the exact number of HSC was not possible
because of the inherent variability in the technique of human
bone marrow aspiration. We also observed, on average, an age-
associated increase, albeit not statistically significant, in the
frequency of multipotent progenitors (MPP; Lin−CD34+CD38−
CD90−CD45RA−) (33) (SI Appendix, Fig. S2). We further investi-
gated the age-associated expansion of human HSC by evaluating
Y) and DNA (Hoechst 33342) dyes (Fig. 1C and SI Appendix, Fig.
Y low, and likely in the quiescent G0phase of the cell cycle,
compared withelderly HSC, ofwhich there is a greaterpercentage
that are Pyronin Y high, and likely in nonquiescent G1, S, or G2
phases (Fig. 1C and SI Appendix, Fig. S3 A and B).
Because HSC differentiate into mature blood cells via a suc-
cession of committed progenitors, we next examined these pop-
ulations in young and elderly bone marrow samples to determine
whether age-associated increases in human HSC frequency cor-
responded to changes in frequency of human myeloid and lym-
phoid progenitors. We did not detect any differences in the
frequency of the immunophenotypic common myeloid progeni-
tors (CMP; Lin−CD34+CD38+CD123+CD45RA−), granulocyte-
CD45RA+), and megakaryocyte-erythrocyte progenitors (MEP;
Lin−CD34+CD38+CD123−CD45RA−) (34) from young and el-
derly bone marrow (SI Appendix, Fig. S4 A–C). However, elderly
bone marrow did exhibit a relative decrease in the frequency of
CD127+; Fig. 2 and SI Appendix, Fig. S5). Therefore, whereas the
lymphoid progenitors decline.
To determine the changes in the developmental potential of
aged human HSC, we analyzed the ability of young and elderly
HSC to generate myeloid and lymphoid progeny in vitro, and
engraft and differentiate in vivo. We used FACS to isolate young
and elderly immunophenotypic human HSC. FACS-purified HSC
were cocultured with AC6.2.1 cells, which can act as a surrogate
for normal bone marrow stroma in supporting both myeloid and
B-lymphoid differentiation of human HSC (24). We determined
by flow cytometry the percentage of B cells (CD19+) and myeloid
cells (CD33+and/or CD13+) generated by young and elderly
human HSC (Fig. 3A). Young HSC, compared with elderly HSC,
cultured for 14 d on AC6.2.1 cells yielded greater numbers, albeit
not statistically significant, of human CD45+cells per HSC,
suggesting greater plating efficiency (SI Appendix, Fig. S6A).
Experiments using single HSC from either young or elderly
bone marrow samples plated on AC6.2.1 did not yield quanti-
fiable colonies at any appreciable frequency. Notably, we found
that elderly HSC exhibit significantly diminished capacity to give
rise to lymphoid B lineage cells, resulting in an increased pro-
portion of myeloid cells being generated per HSC cultured
on AC6.2.1, and an increased myeloid-to-lymphoid ratio (Fig.
3B). The decreased efficiency in the generation of lymphoid B
lineage cells by elderly HSC may be a mechanism behind the
to young. (A) Gating strategyand flow cytometric profile of HSC (Lin−, CD34+,
CD38−, CD90+, CD45RA−) in representative hematopoietically normal young
(Left) and elderly (Right) bone marrow samples. The left panels for each
sample are gated on lineage negative (Lin−) live cells, and the right panels
are gated on Lin−CD34+CD38−live cells. (B) Summary of HSC as frequency of
total Lin−CD34+population from multiple young (n = 13) and elderly (n = 11)
bone marrow samples. *P < 10−7. (C) Summary of quiescent G0(Hoechst
33342low, Pyronin Ylow, correlating with 2N DNA and low levels of RNA) and
non-G0(Pyronin Yhigh, correlating with 2N to 4N DNA and higher levels of
RNA) HSC frequency out of total HSC from multipleyoung (n = 13) andelderly
(n = 8). # P < 0.013. Error bars represent standard deviation.
Increased frequency of HSC in normal elderly bone marrow compared
pared to young. (A) Gating strategy and flow cytometric profile of CLP (Lin−,
CD34+, CD127+) in representative hematopoietically normal young (Left) and
elderly (Right) bone marrow samples. The left panels for each sample are
gated on lineage negative (Lin−) live cells, and the right panels are gated on
Lin−CD34+live cells. (B) Summary of CLP as frequency of total Lin−CD34+
population from multiple normal young (n = 10) and elderly (n = 7) bone
marrow samples. *P < 2.0 × 10−4.
Decreased frequency of CLP in normal elderly bone marrow com-
Pang et al.PNAS
| December 13, 2011
| vol. 108
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observed myeloid-biased behavior of elderly HSC. Additionally,
this reduction in lymphopoiesis potential may account in part
for the decreased plating efficiency of elderly HSC, because the
number of myeloid cells generated in AC6.2.1 culture per HSC
is similar between young and elderly HSC (SI Appendix, Fig.
S6A). We did not observe significant differences in the ability of
young and elderly HSC to form myeloid and erythroid colonies
in methylcellulose culture (SI Appendix, Fig. S6B), further sug-
gesting that myeloerythroid differentiation capacity is preserved
in elderly HSC.
We also isolated immunophenotypic human HSC from 10 young
and nine elderly bone marrow samples, and transplanted each of
them i.v. into an immunodeficient NOD.Cg-PrkdcscidIl2rgtm1Wjl/
SzJ (NSG) pup. At 16 wk posttransplant, we found that six of 10
mice (60%) transplanted with young HSC, and six of nine mice
(66%) transplanted with elderly HSC, contained human CD45+
cells in the bone marrow. Mice successfully engrafted with el-
derly human HSC, compared with young human HSC, had lower
human chimerism per HSC transplanted (Fig. 3C). Additionally,
bone marrow of mice engrafted with elderly HSC, compared with
young HSC, contained a higher myeloid-to-lymphoid progeny
(CD33+and/or CD13+to CD19+) ratio (Fig. 3D), suggesting
that xenotransplanted elderly HSC, compared with young HSC,
generate myeloid progeny more efficiently than lymphoid prog-
eny. The data may reflect an inherent myeloid bias within the
elderly compared with young HSC population, and the process of
lineage specification in human hematopoiesis likely begins in
diverse stem cells. Spleens from engrafted mice contained human
CD45+CD3+T cells, but their frequencies were too low to
identify any significant differences, and bone marrow from en-
grafted mice contained human glycophorin A+erythroid cells
and human CD41/61+platelets (SI Appendix, Fig. S7).
strategy and flow cytometric profile of representative progeny derived from FACS-purifed HSC from hematologically normal young (Left) and elderly (Right)
bone marrow samples cultured for 14 days on AC6.2.1 stromal cell line. The panels for each sample are gated on human CD45+live cells. (B) Summary of CD13+
and/or CD33+myeloid versus CD19+B-lymphoid distribution generated from 50−200 HSC from multiple normal young (n = 8) and elderly (n = 6) bone marrow
samples cocultured with AC6.2.1 stromal cell line. *P < 0.011. (C) Summary of bone marrow engraftment as measured by percent human chimerism per 500
transplanted HSC from unique young (n = 10) and elderly (n = 9) bone marrow samples. Each diamond represents an individual mouse transplanted with HSC
from unique human bone marrow samples, and the bar indicates the average. On average, mice transplanted with young human HSC developed approximately
twofold more human chimerism than mice transplanted with elderly human HSC, but this difference was not statistically significant due to the numbers of mice
transplanted with young (n = 4) or elderly (n = 3) human HSC, which did not have any detectable chimerism. However, the approximately twofold difference in
percent human chimerism between mice successfully engrafted with either young (n = 6) or elderly (n = 6) human HSC is statistically significant (P < 0.02). (D)
Summary of human CD13+and/or CD33+myeloid versus CD19+B-lymphoid distribution from bone marrow of mice successfully engrafted with young (n = 6) or
elderly (n = 6) human HSC. Each diamond represents an individual mouse transplanted with HSC from a unique individual and the bar indicates the average. On
average, the myeloid-to-lymphoid ratio was increased in the mice transplanted with elderly HSC by 14-fold. #P < 0.004. Error bars represent standard deviation.
Diminished lymphoid versus myeloid differentiation capacity of HSC from normal elderly bone marrow compared to young bone marrow. (A) Gating
| www.pnas.org/cgi/doi/10.1073/pnas.1116110108Pang et al.
To identify changes in gene expression that may underlie the
differences in frequency and developmental potential of young
and elderly HSC, we used FACS to sort HSC from 14 young and
eight elderly bone marrow samples for transcriptional profiling
(>95% purity; SI Appendix, Fig. S8). We also obtained gene ex-
pression data for five midage (42–61 y of age) bone marrow
samples. Using the significance analysis of microarray (SAM) al-
[false discovery rate (FDR) < 30%; SI Appendix, Table S1]. We
confirmed the changes in expression of a subset of genes in sorted
HSC from four young and four elderly independent samples using
quantitative RT-PCR (Fig. 4A). Using Ingenuity Pathways Anal-
ysis (IPA) software, we found that this set of age-regulated genes
significantly enriched for transcriptional networks and biological
functions associated with cell-cycle, cell growth and proliferation,
and hematopoietic development (SI Appendix, Fig. S9 A–C). We
also found that elderly HSC up-regulate genes associated with
signaling pathways, including ERK/MAPK and GM-CSF signal-
ing, that are involved in the expansion and proliferation of he-
matopoietic stem and progenitor compartments (SI Appendix, Fig.
S9D). Interestingly, biological functions and pathways associated
with DNA repair and cell death are concurrently enriched (SI
Appendix, Fig. S9C). Additionally, we found elderly HSC up-reg-
ulate several genes that have been implicated in human hemato-
poietic myeloid malignancies, including Aurka, Fos, Hoxa9, Myc,
and Trim13 (Fig.4A and SI Appendix, Table S2).In contrast, young
HSC express approximately twofold-higher levels of Maff (Fig. 4A
and SI Appendix, Table S2), which is involved primarily in
translocations found in lymphoid leukemias more commonly seen
in young patients. We also found, using IPA, that the age-regu-
lated genes in HSC are significantly enriched for those that are
involved in acute myeloid leukemia signaling (SI Appendix, Fig.
S9D). In addition, we found that elderly HSC primarily up-regu-
late genes that specify myeloerythroid fate and function (Fig. 4B),
and down-regulate genes associated with lymphopoiesis (Fig. 4C).
These findings that the age-associated increased expression of
myeloid-specification gene SELP and decreased expression of
lymphoid-specification genes FLT3 and SOX4 in human HSC
have also been observed in mouse HSC (2, 6, 36). The increase in
transcription of myeloid lineage-specific genes in the elderly hu-
man HSC population correlates with our in vitro and in vivo
results, suggesting that the lineage biases of aged immunopheno-
typic human HSC is in part transcriptionally defined.
In this study, we have characterized the age-associated effects on
human hematopoiesis at the level of the stem cell. In aged indi-
viduals, we have found that immunophenotypic human HSC, sim-
ilar tomouse HSC,areincreasedinfrequency. Because the process
of bone marrow aspiration often allows for the inclusion of a small
amount of peripheral blood in the acquired sample, and because
the CD34+population is found primarily in the bone marrow, we
calculated the frequency of immunophenotypic human HSC, as a
percentage of CD34+cells, as the best proxy for the frequency of
HSC in bone marrow. The increased variability in the frequency of
immunophenotypic human HSC as a percentage of total bone
marrow mononuclear cells is potentially due in part to differing
amounts of peripheral blood cells within the acquired sample.
In addition, we have found that elderly immunophenotypic hu-
man HSC have poorer engraftment efficiency and are relatively
more myeloid-biased than young HSC. The relative decrease in
frequency of CLP in human bone marrow combined with the rel-
ative lossofB-cellpotential andcorrespondingincrease ofmyeloid
potential of immunophenotypic HSC both in vitro and in vivo
suggest that lineage bias of the HSC population changes with age.
We were unable to measure significant differences in other line-
ages due to low chimerism; more robust in vitro and in vivo models
for quantitative assessment of T-cell, erythroid, and megakaryo-
cytic potentials of human HSCs will be needed to more thoroughly
assess the lineage potential of human HSCs and confirm our hy-
pothesis. Efficientfunctional assays ofthe engraftmentand lineage
potential of single human HSC would be the most ideal method to
characterize aging human HSC, because the immunophenotypic
human HSC population we have analyzed is likely heterogeneous,
containing distinct subsets of HSC and potentially non-HSCs.
Nevertheless, by examining a highly purified population that is
significantly enriched for bone marrow-derived human HSC, we
have begun to identify subtle but important age-associated prop-
erties of the HSC population, in terms of its frequency and de-
velopmental potential, which would have been missed if one
looked at more heterogeneous hematopoietic progenitor pools.
Our data indicate that human hematopoietic aging, similar to
mouse hematopoietic aging, is associated with changes in human
HSC gene expression that reflect the quantitative and functional
alterations seen in elderly HSC. The increase in elderly HSC fre-
quency may be partly due to increased frequency of HSC in active
cell-cycle phases. Elderly HSC up-regulate genes associated with
cell-cycle, cell growth and proliferation, and hematopoietic de-
velopment, corresponding well with the increased proportion of
elderly HSC that we observed to likely be in more active cell-cycle
phases. However, this increase in HSC frequency does not nec-
essarily translate into improved HSC function, supported by our
finding that elderly HSC do not have as high engraftment effi-
ciency in our xenotransplantation model.
We and others have proposed that stem cells, due to their in-
DNA damage over the life of the organism, and can therefore ac-
cumulate the multiple genetic/epigenetic events required for a
normal cell to become a cancer cell (37–40). Our gene expression
marrow reveals transcriptional differences reflecting myeloid lineage-bias of
elderly HSC. (A) Validation of microarray data by quantitative RT-PCR: average
fold-change in the expression of selected genes as determined by microarray
analysis (14 young and 8 elderly HSC samples) and quantitative RT-PCR (4
young and 4 elderly HSC samples; independent of samples analyzed by micro-
arrays). Error bars represent standard deviation. Heat maps reflecting expres-
sionlevels of (B) myeloid-specific and (C) lymphoid-specific age-regulatedgenes
that are significantly differentially expressed between young and elderly HSC.
Gene expression profiling of HSC from normal elderly and young bone
Pang et al. PNAS
| December 13, 2011
| vol. 108
| no. 50
data shows that elderly HSC up-regulate genes associated with
DNA repair and cell death, possibly indicating that elderly HSC
have activated cell-cycle checkpoints in response to DNA damage.
Even though more elderly HSC may be in the process of pro-
liferating, we speculate that they may also be arrested at cell-cycle
checkpoints, perhaps due to the presence of DNA damage, for
may lead to increased recruitment of quiescent HSC into the cell
In this study, we also showed that the decline in lymphopoiesis
with age can be traced to the behavior of the stem cell, and the
transcriptional up-regulation of genes that specify myeloid-line-
age differentiation likely underlies the myeloid skewing observed
in elderly HSC. This change in developmental potential observed
within the HSC population during aging could be due to (i) all
HSC changing from balanced myeloid-lymphoid potential to
myeloid-biased with age or (ii) intrinsically myeloid-biased HSC
outcompeting balanced-potential HSC during aging. In mice,
small numbers of myeloid-biased HSC can be found among
balanced-potential HSC in young 2-mo-old mice (8, 11, 12),
suggesting that the young mouse HSC pool may contain lineage-
biased clones that compete for niches and expansion signals. The
young human HSC population may similarly contain clones of
lineage-biased cells, the selection of which, during aging, results
in the predominance of myeloid-biased HSC in the elderly. This
myeloid-biased skewing of elderly HSC lineage potential that we
have observed may be one mechanism behind the increased
frequency of myeloid disorders and malignancies in elderly
people. Another factor that may contribute to the increased in-
cidence of myeloid malignancies with age is that elderly human
HSC up-regulate genes implicated in myeloid malignancies, such
as Aurka, Fos, Hoxa9, Myc, and Trim13. Although these genes
likely play roles in the normal maintenance and functions of
HSC, we speculate that the increased transcription of these
genes may potentially facilitate translocations to these loci and
thereby malignant transformation in elderly bone marrow. HSC
in elderly bone marrow, having accumulated a lifetime of ge-
nomic insults and being transcriptionally as well as functionally
myeloid biased, may also be more likely to contribute to the
development myeloid, as opposed to lymphoid, diseases.
Changes within the human HSC population during aging could
also be influenced by alterations in the interactions between HSC
and their aging niches. In the mouse, there is evidence to suggest
that the young and elderly mouse HSC populations respond dif-
ferently to cytokines such as IL-7 and TGF-β (9, 12). In young and
elderly human HSC, we observed differential expression of cy-
tokine receptors and pathways, including enrichment of the ERK/
MAPK signaling and GM-CSF signaling pathways in elderly HSC,
which may be physiological responses by different subtypes of
lineage-biased human HSC to the aging hematopoietic environ-
ment. In particular, the increase in elderly human HSC frequency
and their myeloid bias may reflect the hematopoietic system’s
attempt to maintain homeostasis, ensuring adequate functional
mature progeny. We speculate that the inability of elderly human
HSC to maintain homeostasis contributes to age-associated
cytopenias, including anemias and dysplasias.
Notably, the results from our functional analysis and gene ex-
pression profiling of young and elderly human HSC significantly
parallel the data we and others have generated on young and
elderly mouse HSC (2, 6, 36). Both aged human and mouse HSC
are increased in frequency, and they are transcriptionally and
functionally myeloid-biased in their differentiation potential. Not
surprisingly, the set of differentially expressed genes between
young and elderly human HSC shares overlap with the set of
differentially expressed genes between young and elderly mouse
HSC. These similarities strongly suggest that the biological pro-
cesses that cause the hematopoietic aging phenotype are similar
between human and mouse, and that mouse hematopoietic aging
is a reasonable model of human hematopoietic aging.
Our data directly implicate the human HSC and their age-
associated alterations in the frequency, function, and gene ex-
pression as vital contributors to the aging in the human hemato-
poietic system. Further studies will address the pathways involved
in the aging of the healthy human HSC population and also
characterize HSC from age-associated hematopoietic diseases to
better understand the processes involved in changing healthy el-
derly HSC into diseased elderly HSC.
Human Samples. Normal young human bone marrow mononuclear cells were
purchased from AllCells, Inc. Normal young and elderly human bone marrow
samples were obtained from hematologically normal donors at the Stanford
Medical Center with informed consent, according to an institutional review
board (IRB)-approved protocol (Stanford IRB nos. 5112 and 10831). We an-
alyzed a total of 15 elderly (ages 65–85), 28 young (ages 20–31), and 5
midage (ages 42–61) normal bone marrow samples. Peripheral blood com-
plete blood count values, from samples for which data are available, can be
found in SI Appendix, Table S3. Mononuclear cells from bone marrow
samples were prepared using Ficoll-Paque PLUS (GE Healthcare) and either
analyzed/sorted fresh or cryopreserved in 90% FBS, 10% DMSO in liquid
nitrogen. There is inherent variability in the technique of human bone
marrow aspiration, during which peripheral blood may be aspirated along
with bone marrow; therefore, the mononuclear cell fraction obtained from
each aspiration may contain a small but unpredictable percentage of pe-
ripheral blood mononuclear cells in addition to bone marrow mononuclear
cells. Estimates of bone marrow cellularity were determined by examination
of bone marrow core biopsies. Human CD34-positive cells were enriched
using magnetic beads (Miltenyi Biotec; Stemcell Technologies).
Flow Cytometry Analysis and Cell Sorting. The following panel of antibodies
(Caltag/Invitrogen and BD Biosciences) was used for analysis and sorting of
human hematopoietic stem and progenitor populations: PE-Cy5–conjugated
anti-human lineage markers (anti-CD2, RPA-2.10; anti-CD3, S4.1; anti-CD4,
S3.5; anti-CD7, CD7-6B7; anti-CD8, 3B5; anti-CD10, 5-1B4; anti-CD11b,
ICRF44; anti-CD14, TU.K.4; anti-CD19, SJ25-C1; anti-CD20, 13.6E12; anti-
CD56, B159; anti-GPA, GA-R2), PB-conjugated anti-CD45RA, MEM56; PE-Cy7–
conjugated anti-CD38, HIT2; FITC-conjugated or Alexa Fluor 700-conjugated
anti-CD90 (Thy-1), 5E10; PE-conjugated or FITC-conjugated anti-CD123; PE-
conjugated anti-CD127, hIL-7R-M21.
The following panel of antibodies was used for analysis of differentiated
human hematopoietic populations and human engraftment/chimerism: PB-
conjugated CD45, HI30; APC-conjugated anti-CD34, 8G12; Alexa Fluor 750-
CD13, TK1; PE-conjugated CD33, P67.6; PE-Cy5–conjugated GPA, GA-R2; FITC-
conjugated CD41a, HIP8. The following panel of antibodies (eBiosciences) was
used to identify mouse leukocytes and red blood cells, respectively: Alexa Fluor
488- or PE-Cy7–conjugated CD45.1, A20.1.7; PE-Cy5– or PE-Cy7–conjugated
Ter119. Single-cell suspensions were prepared using standard methods from
For analyses and sorting, except otherwise noted below, cells were stained
with the appropriate antibody combinations for 30–60 min on ice, and dead
cells were excluded by propidium iodide staining. Gating strategy used
to separate CD90+from CD90−, CD45RA+from CD45RA−, CD123+from
CD123−, and CD127+from CD127−populations was fluorescence minus one.
106cells/mLofHBSS medium(10% FCS, 20mM Hepes, 1 g/Lglucose,and50μg/
mL verapamil) and incubated for 30 min at 37 °C with 20 μg/mL Hoechst 33342
(Invitrogen); 1 μg/mL Pyronin Y (Sigma-Aldrich) was added and cells were in-
cubated for another 10 min at 37 °C, stained with the appropriate antibody
combination foridentificationofHSCfor 30min onice,washed,andanalyzed.
Gating strategy used to identify quiescent G0(Hoechst 33342low, Pyronin Ylow,
correlating with 2N DNA and low levels of RNA) and non-G0(Pyronin Yhigh,
correlating with 2N–4N DNA and higher levels of RNA) populations was first
delineated based on Lin−CD34+population from the same samples (SI Ap-
pendix, Fig. S3B), and identical gates were used to identify G0and non-G0
subsets within the HSC population (SI Appendix, Fig. S3A).
Cells were analyzed and sorted using a FACSAria II cytometer (BD Bio-
sciences). A total of 50–300 HSC were sorted for in vitro assays, 500–2,000
HSC were sorted for in vivo assays, and ∼1,000–10,000 HSC were sorted for
RNA purification. Analysis of flow cytometry data were performed using
FlowJo Software (Treestar).
In Vitro Assays: Methylcellulose and AC6.2.1 Coculture. Methylcellulose colony
formation was assayed by sorting 300 cells into individual wells of a six-well
plate, each containing 3 mL of complete methylcellulose (Methocult GF+
| www.pnas.org/cgi/doi/10.1073/pnas.1116110108Pang et al.
H4435; Stemcell Technologies). Plates were incubated for 12–14 d at 37 °C, Download full-text
and colonies then scored based on morphology.
To analyze the myeloid and B-cell lymphoid potential of HSC (20, 21, 24),
50–200 HSC were sorted into individual wells of a 96-well plate containing
semiconfluent AC6.2.1 stromal cells (42) in Iscove’s modified Dulbecco’s
medium, GlutaMAX, penicillin/streptomycin, nonessential amino acids, and
sodium pyruvate. Plates were incubated for 14 d at 37 °C in 5% oxygen, and
cells then analyzed by flow cytometry.
Mouse Transplantation. NSG mice obtained originally from the Jackson Lab-
oratory were bred in a specific pathogen-free environment according to
a protocol approved by the Stanford Administrative Panel on Laboratory
Animal Care. P0–P2 newborn pups were preconditioned with 100 rads of
γ-irradiation up to 24 h before transplantation (33, 43). A total of 500–2,000
FACS-purified HSC were resuspended in PBS containing 2% FCS and trans-
planted i.v. via the anterior facial vein using a 30- or 31-gauge needle.
Statistical Analysis. Student t test was performed using Excel (Microsoft).
RNA Purification, Amplification, and Microarray Analysis. Total RNA was
extracted using TRIzol (Invitrogen) or Ambion RNA Isolation Kit (Applied
Biosystems by Life Technologies) according to the manufacturer’s protocols
and treated with DNase I (Qiagen). All RNA samples were quantified with
the RiboGreen RNA Quantitation Kit (Molecular Probes), subjected to re-
verse transcription, two consecutive rounds of linear amplification, and
production and fragmentation of biotinylated cRNA (Affymetrix). Fifteen
micrograms of cRNA from each sample was hybridized to Affymetrix HG
U133 Plus 2.0 microarrays. Hybridization and scanning were performed
according to the manufacturer’s instructions (Affymetrix). Raw data from all
samples are available from the Gene Expression Omnibus (GEO) database,
www.ncbi.nlm.nih.gov/geo (accession no. GSE32719).
Raw data were normalized using the standard robust multichip average al-
gorithm, together with 21,701 Affymetrix U133 Plus 2.0 human microarrays
downloaded from GEO, according to methods previously described (44). Probe
sets were identified to be present, and their associated transcripts expressed in
elderly or young HSC if the mean of the normalized values of the probe sets
of either group was greater than the threshold value calculated using the
StepMiner algorithm, as previously described (45). The normalized data from
probe sets that were determined to be present were then used in SAM (35) and
Ingenuity Pathways Analysis (Ingenuity Systems). The categorization of genes
into lymphoid and myeloid groupings was done based on evaluation of relevant
literature as well as available gene expression profiling data of human and
maps were generated using HeatMapViewer (GenePattern; Broad Institute).
ACKNOWLEDGMENTS. The authors thank Renee Mehra for administrative
and logistical support; Ravi Majeti, Christopher Park, Matthew Inlay, and
Charles Chan for helpful advice and discussions; Theresa Storm and Libuse
Jerabek for excellent laboratory management; Ken Cheung for statistical
advice; and the Stanford Functional Genomics Facility for array processing
services. Support for this work was provided by the Stanford Medical
Scientist Training Program (W.W.P.), a grant from the Siebel Stem Cell
Institute and the Thomas and Stacey Siebel Foundation (to D.S.), and
National Institute of Aging Grant R01AG029124 (to S.L.S. and I.L.W).
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| vol. 108
| no. 50